Cosmin Ștefan Ciocan
0bddf6a6e6
* Add option to give nvcc extra arguments * Add test for nvcc options that changes c++ dialect from c++17 to c++14 * Add make and the english language pack to devcontainer to be able to build the documentation * Update documentation config to automatically import the current version of the package * Document new --compiler-args argument * Improve tests coverage by testing for bad arguments and the error output during a failed compilation * Add IPython to docs requirements to allow the __version__ import for readthedocs env * Change devcontainer base image to have the latest CUDA toolkit * Mock the nsight compute tool with a bash script * Add test to compile with opencv * Add new page to documentation that contains a new notebook that explains compiling with external libraries * Add autodocstring vscode extension to devcontainer * Add function that modifies the default profiler/compiler arguments to allow reusing them in multiple magic command calls * Update pylint exceptions * Update contributing instructions * Change version from 1.0.3 to 1.1.0 due to adding features in a backward-compatible manner * Install latest CUDA toolkit on the test runner to pass the OpenCV compilation test * Install opencv in test runner and update code coverage install * Add CUDA bin to PATH in test and coverage runners * Add cuda bin to path variable in .bashrc * Update way to set environment variable PATH in github action * Change devcontainer base image back to ubuntu:22.04 to match the environment from the test runner * Add option to choose between NSYS and NCU profilers * Add tests for choosing the profiler * Add isort config to help it find local modules so they are not considered 3rd party libraries * Replace experimental-string-processing black formatter config with enable-unstable-feature as it was removed in version 24.1.0 * Search for profiling tools executable paths when they are required * Install dev dependencies in editable mode * Add documentation for using Nsight Systems instead of the default Nsight Compute profiling tool * Fix cuda typo * Mention Nsight Systems in README.md
3.8 KiB
nvcc4jupyter: CUDA C++ plugin for Jupyter Notebook
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nvcc4jupyter is a Jupyter Notebook plugin that provides cell and line magics to allow running CUDA C++ code from a notebook. This is especially useful when combined with a hosted service such a Google's Colab which provide CUDA capable GPUs and you can start learning CUDA C++ without having to install anything or even to own a GPU yourself.
Table of Contents
Main Features
Here are just a few of the things that nvcc4jupyter does well:
- Easily run CUDA C++ code
- Profile your code with NVIDIA Nsight Compute or Nsight Systems
- Compile your code with external libraries (e.g. OpenCV)
- Share code between different programs in the same notebook / split your code into multiple files for improved readability
Install
The installer for the latest released version is available at the Python Package Index (PyPI).
pip install nvcc4jupyter
Usage
First, load the extension to enable the magic commands:
%load_ext nvcc4jupyter
Running a quick CUDA Hello World program:
%%cuda
#include <stdio.h>
__global__ void hello(){
printf("Hello from block: %u, thread: %u\n", blockIdx.x, threadIdx.x);
}
int main(){
hello<<<2, 2>>>();
cudaDeviceSynchronize();
}
For more advanced use cases, see the documentation.
Documentation
The official documentation is hosted on readthedocs.
License
Contributing
The recommended setup for development is using the devcontainer in GitHub Codespaces or locally in VSCode.
If not using the devcontainer you need to install the package with the development dependencies and install the pre-commit hook before commiting any changes:
pip install -e .[dev]
pre-commit install